Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of t...
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ftunivtoronto:oai:localhost:1807/73963 2023-05-15T15:31:38+02:00 Genetic stock identification of Atlantic salmon and its evaluation in a large population complex Vähä, Juha-Pekka Erkinaro, Jaakko Fålkegard, Morten Orell, Panu Niemelä, Eero 2016-07-04 http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 unknown NRC Research Press (a division of Canadian Science Publishing) 0706-652X http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 Article 2016 ftunivtoronto 2020-06-17T12:00:53Z Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (Global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed stock fisheries. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. Article in Journal/Newspaper Atlantic salmon University of Toronto: Research Repository T-Space Teno ENVELOPE(25.690,25.690,68.925,68.925) |
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Open Polar |
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University of Toronto: Research Repository T-Space |
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ftunivtoronto |
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unknown |
description |
Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (Global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed stock fisheries. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. |
format |
Article in Journal/Newspaper |
author |
Vähä, Juha-Pekka Erkinaro, Jaakko Fålkegard, Morten Orell, Panu Niemelä, Eero |
spellingShingle |
Vähä, Juha-Pekka Erkinaro, Jaakko Fålkegard, Morten Orell, Panu Niemelä, Eero Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
author_facet |
Vähä, Juha-Pekka Erkinaro, Jaakko Fålkegard, Morten Orell, Panu Niemelä, Eero |
author_sort |
Vähä, Juha-Pekka |
title |
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
title_short |
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
title_full |
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
title_fullStr |
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
title_full_unstemmed |
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex |
title_sort |
genetic stock identification of atlantic salmon and its evaluation in a large population complex |
publisher |
NRC Research Press (a division of Canadian Science Publishing) |
publishDate |
2016 |
url |
http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 |
long_lat |
ENVELOPE(25.690,25.690,68.925,68.925) |
geographic |
Teno |
geographic_facet |
Teno |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
0706-652X http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 |
_version_ |
1766362173965074432 |